scAMACE (integrative Analysis of single-cell Methylation, chromatin ACcessibility, and gene Expression)
Python implementation (both CPU and GPU version) to a model-based approach to the joint analysis of single-cell data on chromatin accessibility, gene expression and methylation.
You can install the released version of scAMACE_py from Github:
pip install git+https://github.com/cuhklinlab/scAMACE_py
EM: Expectation-maximization (EM) implementation on CPU of scAMACE.
E_step: Perform E-step (i.e. calculate the expectations of missing data) for one iteration in the EM algorithm on CPU.
EM_gpu: Expectation-maximization (EM) implementation on GPU of scAMACE.
E_step_gpu: Perform E-step (i.e. calculate the expectations of missing data) for one iteration in the EM algorithm on GPU.
generate_sim_data: Generate simulation data x, y and t.
Please refer to the vigenette with several examples for a quick guide to scAMACE_py package.
Jiaxuan Wangwu, Zexuan Sun, Zhixiang Lin: scAMACE: Model-based approach to the joint analysis of single-cell data on chromatin accessibility, gene expression and methylation.